def test_bpr_predictions():
bpr = BPR(10, 100, 50)
train_data = zip(randint(100, size=1000), randint(50, size=1000))
bpr.train(train_data, epochs=1)
assert_equal(bpr.predictions(0).shape, (50,))
assert_equal(bpr.prediction(0,0), bpr.predictions(0)[0])
assert_equal(len(bpr.top_predictions(0, topn=20)), 20)
bpr.train(training_array[split3:], epochs=1)
#bpr.train(training_array, epochs=4)
print(" epoch", epoch, " took ", str(time.time() - runtime),
"seconds to run..")
print("testing")
tester = Tester()
prediction_batch = []
print("getting user predictions for testing")
runtime = time.time()
user_predictions = []
for user in users:
user_predictions.append(bpr.top_predictions(user, topn=20))
print(" predictions found in", str(time.time() - runtime), "seconds")
print(user_predictions[1])
print(user_predictions[100])
print(user_predictions[300])
print(user_predictions[600])
print(user_predictions[800])
print("calculating test scores")
for i in range(len(x)):
sequence_predictions = []
for j in range(sl[i]):
sequence_predictions.append(user_predictions[i])
prediction_batch.append(sequence_predictions)
